基于图像识别的中国画真伪鉴别研究
发布时间：2019-04-02 01:49
【摘要】：中国画作为世界艺术宝库中独树一帜的艺术创作形式,也是我国传统文化艺术的重要组成部分。随着中国画逐渐步入国际拍卖市场,近几年出现了大量的赝品。所以,如何准确的判断一幅中国画作品的真伪已成为目前中国画发展中面临的一大难题。传统的中国画真伪鉴别主要是专家通过自身已有的经验,根据作品的笔法、墨法以及所处年代,对画作进行感性判断,但是,这种方法极易受主观因素干扰,并且缺乏客观的、可量化的鉴别指标。针对上述问题,论文使用图像处理计算机视觉等技术,并结合一些可量化的中国画真伪鉴别指标,设计了一种基于图像识别的中国画真伪鉴别方法,以辅助中国画真伪鉴别工作,提高真伪鉴别的可信度。论文主要工作分为以下两个方面。(1)中国画的绘画手法独特,风格类型丰富,基于这一特征设计了一种感兴趣区域(Region Of Interesting,简称ROI)提取的中国画风格特征判别方法。新方法通过提取图像的低阶特征,分析每种特征的ROI特点,再利用最佳权值算法,综合提取图像的特征ROI,最终,根据每种特征在图像中的贡献值来调整权值,以最佳权值所对应的ROI即为特征ROI来作为图像的风格特征。(2)在风格特征区域判别的基础上,设计了一种中国画真伪鉴别方法,由于马尔科夫随机场可以表示当前值与其邻域的关系,因此新方法建立区域级的马尔科夫模型。其中,模型第一层利用改进的置信传播算法迭代递推区域的真伪状态,第二层,根据区域的真伪状态推出对象块的真伪状态,最终,在第三层使用投票法判断出整个作品的真伪状态。最后,在Windows 7操作系统环境下,利用VS2012平台下进行了编程实现,以验证方法的可行性和适用性。
[Abstract]:As a unique form of art creation in the world art treasure house, Chinese painting is also an important part of Chinese traditional culture and art. With the gradual entry of Chinese painting into the international auction market, in recent years a large number of forgeries have emerged. Therefore, how to accurately judge the true or false of a Chinese painting has become a difficult problem in the development of Chinese painting. Traditional Chinese painting identification is mainly through their own experience, according to the painting, ink and age, the painting perceptual judgment, but this method is very vulnerable to subjective factors, and lack of objective, Quantifiable identification index. In order to solve the above problems, this paper designs a Chinese painting authenticity identification method based on image recognition by using image processing and computer vision technology, and combining with some quantifiable identification indexes of Chinese painting authenticity and falsehood. In order to assist the Chinese painting true and false identification work, improve the credibility of true and false identification. The main work of this paper is divided into the following two aspects. (1) the Chinese painting has unique painting techniques and rich style types. Based on this feature, a method of distinguishing the style features of Chinese paintings extracted from (Region Of Interesting, (ROI) is designed. The new method extracts the low-order features of the image, analyzes the ROI characteristics of each feature, and then uses the optimal weight algorithm to extract the feature ROI, of the image synthetically. Finally, the weight is adjusted according to the contribution value of each feature in the image. The ROI corresponding to the optimal weight is taken as the feature ROI as the style feature of the image. (2) on the basis of distinguishing the region of the style feature, a method to distinguish the authenticity and falsehood of Chinese painting is designed. Because Markov random field can represent the relationship between the current value and its neighborhood, a new method is proposed to establish the Markov model at the regional level. The first layer of the model iterates the true and false states of the region using the improved confidence propagation algorithm, and the second layer deduces the true and false states of the object block according to the true and false states of the region, and finally, At the third level, the voting method is used to determine the true or false state of the whole work. Finally, under the environment of Windows-7 operating system, the program is implemented under the platform of VS2012 to verify the feasibility and applicability of the method.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：J212;TP391.41
，
本文编号：2452115
[Abstract]:As a unique form of art creation in the world art treasure house, Chinese painting is also an important part of Chinese traditional culture and art. With the gradual entry of Chinese painting into the international auction market, in recent years a large number of forgeries have emerged. Therefore, how to accurately judge the true or false of a Chinese painting has become a difficult problem in the development of Chinese painting. Traditional Chinese painting identification is mainly through their own experience, according to the painting, ink and age, the painting perceptual judgment, but this method is very vulnerable to subjective factors, and lack of objective, Quantifiable identification index. In order to solve the above problems, this paper designs a Chinese painting authenticity identification method based on image recognition by using image processing and computer vision technology, and combining with some quantifiable identification indexes of Chinese painting authenticity and falsehood. In order to assist the Chinese painting true and false identification work, improve the credibility of true and false identification. The main work of this paper is divided into the following two aspects. (1) the Chinese painting has unique painting techniques and rich style types. Based on this feature, a method of distinguishing the style features of Chinese paintings extracted from (Region Of Interesting, (ROI) is designed. The new method extracts the low-order features of the image, analyzes the ROI characteristics of each feature, and then uses the optimal weight algorithm to extract the feature ROI, of the image synthetically. Finally, the weight is adjusted according to the contribution value of each feature in the image. The ROI corresponding to the optimal weight is taken as the feature ROI as the style feature of the image. (2) on the basis of distinguishing the region of the style feature, a method to distinguish the authenticity and falsehood of Chinese painting is designed. Because Markov random field can represent the relationship between the current value and its neighborhood, a new method is proposed to establish the Markov model at the regional level. The first layer of the model iterates the true and false states of the region using the improved confidence propagation algorithm, and the second layer deduces the true and false states of the object block according to the true and false states of the region, and finally, At the third level, the voting method is used to determine the true or false state of the whole work. Finally, under the environment of Windows-7 operating system, the program is implemented under the platform of VS2012 to verify the feasibility and applicability of the method.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：J212;TP391.41
，
本文编号：2452115
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